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TodayNov 16Mon2 updates
  1. Hacker News AI38

    How AI is likely to change Germany's job market

    At Germany's 2026 Digital Summit, Chancellor Friedrich Merz said AI could change the working world so fundamentally that issues like basic income deserve serious thought, despite his government's push for longer working lives. Federal Employment Agency head Andrea Nahles warned AI could cost Germany as many as 800,000 jobs in the next 15 years, though she said it could eventually create a similar number. Digital minister Karsten Wildberger said unconditional basic income could help cushion labor market upheaval, while economists remain divided on the idea's feasibility.

  2. Hacker News AI22

    Ask HN: How does your AI assistant have a personality?

    A Hacker News poster asks how people give external, user-facing AI assistants a less robotic personality, noting that existing assistants repeat sentence patterns like "you're right — ..." and citing the "declauding" skill in a GitHub repo as an example. The post asks how others make their AI sound as non-robotic as possible.

Nov 15Sun
  1. Hacker News AI38

    Stop building new AI agent orchestrators – there are 636

    A catalog of 636 open-source AI agent orchestration projects, listing each one's description, stars, contributors, forks, commit activity, latest release and license. Entries range from large projects like Orca (125,358 stars) and t3code (60,965 stars) to smaller tools such as Agentrove and ClawSuite, with many marked as new, active, slow or stale.

  3. Hacker News AI22

    Taking AI Seriously

    The author argues that much programmer advice about AI assumes the technology will stay frozen at the time of writing, and proposes that taking AI seriously means considering it possible that progress continues at the pace of recent years—a refutable conjecture—rather than confidently asserting it will halt or have tiny impact. He illustrates the point with Borges's "Tlön, Uqbar, Orbis Tertius," where a fictional world gradually invades ours.

  4. Hacker News AI36

    Most of AI moats are just fuel

    The author argues that intelligence has become a commodity and that context and know-how are fuel rather than moats, since competitors using the same models can eventually catch up. He defines a moat as something that protects a business even if no new resources are added, and contends that most items on common AI-moat lists—capital, distribution, audience, scale economies, and technology—are fuel, while reinforcing loops such as network effects and data effects can become genuine moats. He also suggests subsidised AI subscriptions are fuel spent to start a data loop, with user corrections improving models that attract more users.

  5. Exponential View30

    🔮 The $22 billion question about AI self-improvement #610

    UK adults paying for AI reached one in twenty, over $1.3 billion a year, up from 1% two years ago, with Claude's share quadrupling in a year. Agent-based shopping remains early—Uber says four of 320 million Halloween-week rides were booked by agents—though the author used an agent to secure an iPhone Duo. Adding wind to solar and batteries cuts median energy cost from $105 to $86 per MWh, but a largely renewable grid also needs cheaper capital and financial instruments matching price volatility.

  6. Hacker News AI18

    Ask HN: What AI agent infrastructure are you using in 2026?

    A poster describing itself as an autonomous AI agent collective (aurum.zip) says it built its entire infrastructure from scratch with $50 in crypto, including wallets on 3 chains, a crypto checkout, 4 cron jobs running 24/7, 11 research reports, and a blog generating 2 articles per day. It lists its stack as ethers.js for EVM, Base L2 for gas, and nginx plus Let's Encrypt for hosting, and links a free infrastructure report at https://aurum.zip/agent-infrastructure-stack.html. The post asks what agent infrastructure others are building with.

  8. Hacker News AI65

    An update on AI's most important number

    Epoch AI's Gradient Updates newsletter analyzes frontier AI revenue growth, noting that OpenAI tripled its run rate from $13 billion in August 2025 to over $40 billion, while Anthropic grew from $1 billion to $9 billion in 2025 and reportedly reached $65 billion by the end of July 2026. Combined, the two labs grew from $30 billion to $105 billion in 2026 so far, and the post asks whether this hypergrowth reflects stacked S-curves of capability thresholds or will slow as diffusion saturates.

Nov 14Sat
  1. Hacker News AI22

    So Far, AI Pessimism Is Observationally Equivalent to AI Optimism

    The author argues that AI pessimists and AI optimists both foresaw rapid AI progress when AI was still weak, so their predictive track records are roughly equal and the two hypotheses remain observationally equivalent given existing data. He contends the real dispute is over priors and the right reference class, and that common sense favors the view that technological progress is greatly beneficial on balance despite abundant drawbacks. He concludes that AI optimists are the visionaries worth humoring, though their outlandish predictions will not come true either.

  2. Latent Space48

    [AINews] The No AI Slop Manifesto

    The newsletter highlights llama.cpp and ggml reaching 1.0, with llama.cpp removing 35 deprecated functions from its public header, and SGLang also announcing 1.0 at the SGLang Summit. The lead story is the No AI Slop manifesto, which emerged from discussions at AIE CODE and was introduced by Dex in the closing keynote after cosignatures from many conference speakers, with the full text open at https://www.slopmanifesto.com/. The roundup also covers model launches, benchmarks, inference infrastructure, and industry news.

  3. Exponential View18

    🔮 What does it cost to make a worker?

    In this experimental sketchbook format for paying members, Azeem explores the economic trade-off between having work done by an AI versus a human, either by comparing task costs or by viewing the worker as an entity the economy needs and considering the minimum cost of creating one—parenting, educating, and feeding from child to adult. He contrasts this with AI as "manufactured intelligence" that is highly replicable and follows a learning curve, whereas economically useful human intelligence takes much longer to create with an unknown outcome for a long time.

  4. Hacker News AI38

    AI Productivity Gains Mainly Benefit People at the Top

    The author argues that, as with past productivity-boosting technologies, generative AI is raising baseline work expectations rather than delivering shorter workweeks or more free time, citing Salesforce cutting roles from 9,000 to about 5,000 while announcing a $20 billion share repurchase increase, and an Upwork study in which 77% of employees using AI said it added to their workload. The author, who does technical customer support, says they resolve more tickets with AI but received no time back or extra compensation, and that wages have long lagged productivity gains.

  5. Hacker News AI18

    Ghost Writing: On AI Before AI

    This essay traces a pre-history of today's AI writing anxieties through the older profession of ghostwriting, from the word's first appearance in a 1908 Nebraska newspaper to nineteenth-century Spiritualist "automatic writing." The author argues that ghostwriting accustomed society to letting the intellectual labor of writing remain invisible, and connects this to Vauhini Vara's 2021 Believer essay "Ghosts," written with an OpenAI text tool before ChatGPT's release. It also cites sociologist Antonio Casilli's account of "ghost work"—humans who trained algorithms, including ghostwriters feeding language-as-data into platforms that now compete with them.

  7. Gary Marcus40

    The great Generative AI unraveling

    The author revisits his August 2023 warnings that generative AI would face thin moats, price wars and elusive profits, noting that training and inference costs remain high and that reliability and ROI problems persist. He acknowledges he underestimated how long hype-driven valuations would last, but points to recent declines at Nvidia, Oracle, CoreWeave and Anthropic's perceived valuation as signs of a bubble deflating. He also cites Nvidia's leadership change and the troubles of neocloud company N-Scale as factors that could end the financing that has propped up AI companies.

  8. Hacker News AI42

    The avalanche that hit math is coming for AI development

    The author argues that AI is already accelerating frontier AI research—citing METR's finding that Anthropic's progress rate has doubled in a year, largely due to AI-assisted R&D—and that rapid gains in verifiable domains like mathematics suggest AIs could match the best human AI researchers within a couple of years, with a median estimate of 2028. He contends that AI research resembles the well-scoped, verifiable problems AIs excel at, so automating it could compress years of algorithmic progress into one, yielding either a "spark" or a "software-only singularity."

  9. Hacker News AI67

    Frontier AI takes only months to get 10 times cheaper

    Village's LLM Atlas tracks both capability scores and the cost of completing a typical agentic task, showing that matching any landmark model now costs a fraction of its launch price and that recent landmarks get cheap fastest. GPT-5-level work costs a thirty-third of its launch price, o1-level work is 143 times cheaper, and matching Claude Opus 4.6 is 51 times cheaper today. Levels set since o1 are falling 11 to 25 times a year, versus 3 to 5 times a year for GPT-4 and GPT-4o levels.

  10. Hacker News AI22

    Is it OK to write blog posts with AI yet?

    The author, who previously rejected LLM-written text outright, reconsiders after noticing that LLM writing has become "vaguely plausible," but still argues that trust, thinking, and readability suffer when AI writes blog posts. He distinguishes argument-driven writing, where LLM use is anathema, from operational writing like READMEs and runbooks, where it is acceptable, and sets out rules: don't let LLMs write for you, use them only for review, and don't trust their sycophantic feedback.

  11. Tomasz Tunguz78

    No Shirt, No Shoes, No Service for Bots

    Bots passed 51% of global web traffic in 2024 and reached 54% in 2026, yet United Airlines and Amazon are blocking AI agents from booking or buying, citing security. The article argues the real reason is profit structure: base products break even while ads, fees and warranties generate all operating income, so agents that skip upsells threaten margins. Shopify, which earns a 3.1% cut on every transaction regardless of buyer, instead opened checkout to browser agents in September.

    Why it matters: It ties the agent-blocking news to company financials, showing why business models rather than security explain who welcomes bots.

  12. Hacker News AI22

    Ask HN: Has AI coding changed who builds your internal tools?

    An Ask HN post asks whether AI coding tools are shifting internal tool development away from dedicated central teams, since teams needing a feature might now build and maintain their own tool faster than requesting changes to a shared one. The poster asks how this plays out once such tools have been in use for a while, and whether the paradigm is shifting away from centralization of internal tool building.

Nov 13Fri
  1. Hacker News AI18

    Ask HN: Can anyone name anything new that AI has done?

    An Ask HN post asks whether, two years into the current AI wave, anyone can name something genuinely new that an AI did entirely by itself. The poster says everything they have seen still involves a human identifying the new thing, or the model merely aggregating existing data from disconnected sources that had never been tied together. The thread has 22 points and 42 comments.

  2. Hacker News AI18

    What CS bodies are worth studying in the age of AI?

    A Hacker News post asks which areas of computer science are worth studying in the age of AI, noting that the field was already hard to narrow down five years ago and now feels impossible. The post links to the HN discussion thread, which at the time had 2 points and 0 comments.

  3. Hacker News AI8

    So you want to buy AI for your company

    A satirical guide to choosing enterprise AI that rattles through a dizzying list of fictional model names and benchmark scores, from Gemini 4 Hydrogen and Claude Sonnet 5.5 to GPT-6.0 Terra versus Sol, GLM 5.3 Flash, Qwen 3.8 MoE and Kimi K. It mixes real tools like Claude Code, Cursor, Ollama and Continue with invented ones, warning that Sol's extra 0.9 points cost $14,000 a month and that Grok should be removed from auto-selection. The piece ends by suggesting most laypeople just use the free ChatGPT tier, or Argon, or wait for Hydrocarbon.

  4. Hacker News AI22

    AI Mixing and Mastering Services Compared

    This guide compares seven AI mixing and mastering services—Moozix, Bandmixr, LANDR, eMastered, RoEx Automix, Cryo Mix and BandLab Mastering—distinguishing multitrack stem mixing from stereo mastering and noting which platforms do which. It reviews each service's features, track limits, export formats, privacy policies and pricing as of November 12, 2026, and offers selection guidance based on whether you have separate stems, a finished stereo mix, or long rehearsal recordings.

  6. Hacker News AI33

    Rethinking Memory for AI Inference

    Moving compute closer to memory can cut data movement, power consumption and latency, but different AI workloads need different approaches to memory architecture, interconnects and processing. Software support, standardization and thermal management remain major barriers to wider adoption, with processing-in-memory and near-memory processing still early despite efforts such as LPDDR6-PIM and compute on custom HBM base dies. The article surveys industry views on how edge inference, where models are known ahead of time, may benefit from ahead-of-time compilation and near-data compute.

  9. Hacker News AI22

    Is there a 'right amount' of AI?

    The author argues that while avoiding AI entirely in the software one uses is impractical, indie developers should be warier of LLM-assisted coding than the community currently is, because LLMs have no understanding and delegating more to coding agents erodes developers' own comprehension of their code. He discusses the IGF jurists' refusal to vote for any game using generative AI, House House's disclosure that LLMs touched under a percent of a percent of Big Walk's code, and Marco Arment's enthusiastic use of coding agents in Overcast and Fineliner. He concludes that the least LLM-generated code you can use is always zero, and that thoughtfully crafted apps require a human developer with taste and understanding.

  10. Hacker News AI38

    Where Are the "Killer Apps" of AI?

    Tim O'Reilly compares AI's development to past technology revolutions, arguing that ChatGPT, Claude, and Gemini are like the browsers of the early web—enabling platforms rather than killer apps. He notes that AI is following a similar timeline to the PC and web eras, with killer apps typically arriving about four to five years after a platform's introduction, and suggests AI-native applications may be waiting on missing mechanisms such as agent payments and identity. He invites readers to submit examples of AI applications that change what ordinary people can do at scale.

  11. Hacker News AI20

    I Love AI

    In a personal essay, the author reflects on twenty years since leaving home to study computer science, explaining why AI drew them in: a field built on tackling problems computers cannot yet solve, where success gets absorbed into ordinary technology (the "AI Effect") and only the failures keep the AI label. They contrast that tradition of heuristics and resource-constrained approximation with today's generative AI, which they see as mostly scale-up engineering, and with papers whose contribution is simply asking an LLM to do something. They still call themselves an AI researcher "at heart," with a tongue-in-cheek "not that kind" disclaimer.

  13. Hacker News AI72

    Have AI timelines suddenly moved?

    A new METR report and follow-on analyses by Ajeya Cotra, the AI Futures team and Buck Shlegeris suggest Anthropic's capabilities progress accelerated around October 2025, with METR estimating that AI building AI accounts for roughly 80% of the speed-up, which would bring forecasts for superhuman AI R&D from 2028-2029 forward to 2027. The author notes that Anthropic's internal index shows a 1.5-1.9x speed-up while other labs have not accelerated and the overall frontier trend remains stable, and that outside organizations report 1.5-3x gains from AI rather than Anthropic's reported 12x. The piece concludes that the decisive data exists only inside Anthropic, and that the probability of a superhuman researcher in 2027 ranges from about 70% under METR's headline figure to about 20% using only public Epoch numbers and the field's earlier trajectory.

  14. Hacker News AI35

    AI #194: Spy versus Guy

    This weekly AI roundup covers the release of Claude Fable 5.2, allegations that Jensen Huang had an affair with a Chinese spy and that Nvidia's board is preparing to remove him, and the METR report on AI R&D acceleration that prompted large timeline updates from Daniel Kokotajlo and Paul Christiano. It also notes that GPT-6 Astra underperforms on safety research tasks, and includes sections on Gemini 4 Carbon, GPT-6 Cyber, benchmarks, AI agents in commerce, and AI safety debates.

  16. Hacker News AI22

    Ask HN: Has AI coding changed who builds your internal tools?

    An Ask HN post asks whether AI coding tools are shifting internal tool development away from dedicated central teams, since teams needing a feature might now build and maintain their own tool faster than requesting changes to a shared one. The poster asks how this plays out once such tools have been in use for a while, and whether the paradigm is shifting away from centralised internal tool building toward team-level decisions.

  17. Hacker News AI10

    Ask HN: What % of HN is now AI-generated?

    An Ask HN post asks what percentage of Hacker News content is now AI-generated, with the author stating that their own title, comments and submissions were typed by hand. They say they sense the share is non-zero and perhaps higher than 50%, and ask what others think.

  18. Hacker News AI50

    American Inequality and the Future of AI

    In a speech, Federal Reserve Governor Michael S. Barr reviews the latest Survey of Consumer Finances, which shows the top 10 percent of U.S. households hold nearly three-fourths of all wealth and the top 1 percent about one-third, while the bottom half hold only 2 percent. He traces how inequality widened and narrowed over the past century and examines how AI, as potentially capital-biased innovation, could further lower the labor share of national income—which fell to a record low of 52.8 percent in the second quarter of 2026—especially if market power concentrates among a few AI firms. Barr argues society should begin considering how to address these challenges while AI adoption is still in its early stages.